Storage Retrieval

Download Data Intensive Storage Services for Cloud Environments by Spyridon V. Gogouvitis PDF

By Spyridon V. Gogouvitis

With the evolution of digitized info, our society has develop into depending on companies to extract useful info and improve determination making via members, companies, and executive in all points of lifestyles. consequently, rising cloud-based infrastructures for garage were largely considered the subsequent new release resolution for the reliance on facts increases.

Data extensive garage companies for Cloud Environments provides an outline of the present and strength ways in the direction of info garage companies and its dating to cloud environments. This reference resource brings jointly study on garage applied sciences in cloud environments and numerous disciplines worthy for either pros and researchers.

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Extra resources for Data Intensive Storage Services for Cloud Environments

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Transitional Storage, 4, 11:1–11:28. acm. 1480440 Memopal – Online Backup. ). , & Scheideler, C. (2008). Spread: An adaptive scheme for redundant and fair storage in dynamic heterogeneous storage systems. In Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 1135– 1144). Philadelphia, PA: Society for Industrial and Applied Mathematics. 1347206 Mozy. ). com Nosql Databases. ). org/wiki/NoSQL Parallel Virtual File System (PVFS) Wiki. ). org/wiki/ ParallelVirtualFileSystem Pritchett, D.

IBM’s GPFS SNC (shared nothing cluster) produce was selected for use in VISION Cloud. It fulfills the general requirements of VISION Cloud, namely Scalability, scale out performance, elasticity, and availability. The selection of this technology was heavily influenced by GPFS’s strong commercial track record, as well as IBM HRL’s ability to provide a high level of support if required, and license-free installations for the VISION Cloud test bed. , OneFS, GFS, MS-DFS) or open source solutions that do not carry the maturity and insurance of stability as a product such as GPFS (XtreemFS, PVFS, HDFS, GlusterFS, Lustre).

After much consideration, Cassandra was chosen. The main properties that influenced this decision were its relatively simple installation requirements, OpenSource availability, and its automatic scalability - when adding more servers it will reconfigure itself redistributing load among the servers. RESOURCE ALLOCATION AND ENERGY MANAGEMENT Overview There are a multitude of parameters and considerations involved in the decision of where and when to place data objects and compute tasks (VM execution in general and storlets in the case of VISION Cloud) in a global cloud.

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